Improved distance scaling for sparsified FDPC ensembles
Establish an improved asymptotic minimum-distance scaling for the ensemble of L-sparsified order-s FDPC codes by exploiting the additional parity constraints introduced through sparsification, beyond the minimum-distance guarantee inherited from the parent FDPC code.
References
The distance bound in Theorem~\ref{thm:qfdpc-scaling} is conservative in the sense that it only uses the minimum-distance guarantee of the parent FDPC code. In particular, the additional parity constraints introduced by $L$-sparsification are used to control the rate and stabilizer weight, but their effect on the minimum distance is not exploited. The weight-distribution analysis of Section~\ref{sec:fdpc-extension} suggests that sparsification can substantially suppress low-weight codewords. Therefore, sparsification may yield stronger distance scaling than the parent-code guarantee alone. Establishing an improved asymptotic distance scaling for the sparsified ensemble is therefore left for future work.
Several directions remain open. Deterministic choices of the sparsification and underlying permutations in the FDPC construction, together with a sharper characterization of the good-distance subensemble, could further improve the finite-length constructions and their ML estimates.
Can the sparse protected construction reach linear distance, or select a useful fixed logical sector while retaining sparse checks?